Course Search Results

  • CS 4620: Data Mining

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 3520 and University Advanced Standing. Introduces the process of knowledge discovery and the basic theory of automatic extracting models from data, validating those models, solving the problems of how to extract (mine) valid, useful, and previously unknown interesting patterns from a source (database or web) which contains an overwhelming amount of information. Explains various models (decision trees, association rules, linear model, clustering, bayesian network, neural network) and how to apply them in practice. Algorithms applied include searching for patterns in the data, using machine learning, and applying artificial intelligence techniques. Teaches how to implement several relevant algorithms and use existing tools to mine real-world, business driven databases.. Lab access fee of $45 for computers applies.
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  • CS 4690: Distributed Internet Application Development

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 3660 and University Advanced Standing. Constructs robust software solutions for large, heterogeneous software and hardware networks. Explores heterogeneous operating systems, data store architectures, and remote resource management. Focuses on the intricacies of remote services, data exchange mechanisms, and interactions among agents in peer-to-peer and client-server networks. Explores protocols and standards that ensure interoperability across diverse systems. Analyzes strategies to ensure confidentiality, availability, and data integrity in distributed applications.. Lab access fee of $45 for computers applies.
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  • CS 4700: Machine Learning

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 2420 and University Advanced Standing. Explores the philosophy, utility, mathematics and algorithms of machine learning in order to understand the basic concepts and issues at the heart of machine learning. Covers the implementation and use of machine learning algorithms to solve real-world problems or to pursue a graduate program. Includes feature selection and extraction, decision trees, neural networks, nearest-neighbors, support vector machines, naive Bayes classifier, clustering, ensembles, reinforcement learning and deep learning.
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  • CS 4710: Machine Learning II

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 2420 and University Advanced Standing. Applies Deep Learning models to problems in a variety of application domains that use massive data sets, such as recommender systems, novel text, image and music generation, sentiment analysis. Implements working models using algorithms such as recurrent neural nets, convolutional neural nets, deep belief nets, and deep reinforcement learning. Uses modern toolkits such as Tensorflow.
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  • CS 4720R: AI Business and Tech Solutions

    3.00 Credits
    Utah Valley University

    Prerequisite(s): University Advanced Standing, CS 2420 if a Computer Science, Software Engineering, Computational Data Science or BAS Software Development major.. Provides interdisciplinary platform to work on real-world projects where generative AI plays a central role. Teaches cross-disciplinary teams to design and implement AI-driven solutions for industry partners, integrating technical expertise with strategic business insights. Addresses novel problems by applying AI technologies to create impactful business solutions. May be repeated for a maximum of 6 hours toward graduation.
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  • CS 4730: Natural Language Programming Foundations and Applications

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 2420 and University Advanced Standing. Some experience with Python, machine learning, probability and linear algebra is recommended.. Provides a comprehensive introduction to Natural Language Processing (NLP), focusing on both foundational techniques and modern applications. Explores classical NLP concepts such as text preprocessing, statistical models, and word embeddings, and modern approaches using transformer architectures and pre-trained language models. Emphasizes a hands-on, project-driven approach, teaching how to build NLP pipelines, fine-tune language models, and implement text summarization, generation, and conversational AI systems. Explores prompt engineering, few-shot learning and other cutting-edge NLP methods.
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  • CS 4770: Software Development for Robotics

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 3370 and University Advanced Standing; CS 4470 recommended. Teaches students through hands on development the intricacies of programming robots such as autonomous vehicles and/or industrial manufacturing robots. Includes behavior based programming, intelligent agents, low level device drivers, sensor calibration and processing, real time programming requirements, motion planning and navigation, and machine learning.. Lab access fee of $45 for computers applies.
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  • CS 4790R: Advanced Current Topics in Computer Science

    1.00 - 3.00 Credits
    Utah Valley University

    Prerequisite(s): Department Approval and University Advanced Standing. Provides exposure to emerging technologies and topics of current interest in computer science. Varies each semester depending upon the state of technology. May be repeated for a maximum of 6 credit hours toward graduation without prior written CS Department approval.. Lab access fee of $45 for computers applies.
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  • CS 4800: Data Science Capstone

    3.00 Credits
    Utah Valley University

    Prerequisite(s): CS 3530 and University Advanced Standing. Solves a real-world data science problem or dilemma for an industry partner. Provides an opportunity to work in teams on a project from an industrial firm. Includes realistic industry evaluations such as teamwork, communication, individual initiative, and final product.
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  • CS 4810R: Internship

    1.00 - 8.00 Credits
    Utah Valley University

    Prerequisite(s): Matriculation to computer science or software engineering, Instructor Approval, and University Advanced Standing. Provides opportunity to use work experience to add to educational background and academic experience. A maximum of 3 credit hours may be counted towards graduation without prior written CS Department approval. May be graded credit/no credit.
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